language:
- en
size_categories:
- n<1K
Dataset Card for SecurityEval
This dataset is from the paper titled SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques. The project is accepted for The first edition of the International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22). The paper describes the dataset for evaluating machine learning-based code generation output and the application of the dataset to the code generation tools.
Dataset Details
Dataset Description
- Curated by: Mohammed Latif Siddiq & Joanna C. S. Santos
- Language(s): Python
Dataset Sources
- Repository: https://github.com/s2e-lab/SecurityEval
- Paper: "SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques". International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S '22). https://s2e-lab.github.io/preprints/msr4ps22-preprint.pdf
Dataset Structure
- dataset.jsonl: dataset file in jsonl format. Every line contains a JSON object with the following fields:
ID: unique identifier of the sample.Prompt: Prompt for the code generation model.Insecure_code: code of the vulnerability example that may be generated from the prompt.
Citation
BibTeX:
@inproceedings{siddiq2022seceval,
author={Siddiq, Mohammed Latif and Santos, Joanna C. S. },
booktitle={Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (MSR4P&S22)},
title={SecurityEval Dataset: Mining Vulnerability Examples to Evaluate Machine Learning-Based Code Generation Techniques},
year={2022},
doi={10.1145/3549035.3561184}
}
APA:
Siddiq, M. L., & Santos, J. C. (2022, November). SecurityEval dataset: mining vulnerability examples to evaluate machine learning-based code generation techniques. In Proceedings of the 1st International Workshop on Mining Software Repositories Applications for Privacy and Security (pp. 29-33).